N. A. Mohamed Kamari

Application of evolutionary programming in the assessment of dynamic stability

This paper presents Evolutionary Programming (EP) based optimization technique for estimating synchronizing torque coefficients, Ks and damping torque coefficients, Kd of a synchronous machine. These coefficients are used to identify the angle stability of a system. Initially, a Simulink model was utilized to generate the time domain response of rotor angle under various loading conditions. EP was then implemented to optimize the values of Ks and Kd within the same loading conditions. Validation with respect to eigenvalues determination confirmed that the proposed technique is feasible to solve the angle stability problems.

Computational intelligence approach for SVC-PID controller in angle stability improvement

This paper presents a new optimization approach for tuning conventional PID controller parameters of a static var compensator (SVC) which controls a synchronous machine. SVC is designed and implemented to improve the damping of a synchronous generator. Particle Swarm Optimization (PSO) method based PID controller using SVC is implemented in this study. The study involves the optimization of proportional gain, KP, interval gain, KI and derivative gain, KD of PID controller. Validation with respect to eigenvalues determination and damping ratio confirmed that the proposed technique is effective to improve the angle stability problem.

An evolutionary algorithm approach to design SVC-PI controller for angle stability improvement

This paper presents Evolutionary Programming (EP) based optimization technique for estimating PI controller parameters of a static var compensator (SVC) which controls a synchronous machine. SVC is one type of Flexible AC Transmission Systems (FACTS) device, designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. This paper introduced Evolutionary Programming (EP) optimization method based SVC-PI controller. The study includes the placement of SVC with PI controller, while computational intelligence technique is used in optimizing the parameter values of PI controller: proportional gain, KP and interval gain, KI. Validation with respect to eigenvalues determination and synchronizing and damping torque coefficients (KS and KD) value confirmed that the proposed technique is effective to improve the angle stability problem.

Fuzzy bee colony approach to mitigate congestion problems through TCSC installation for voltage corrective strategy

Application of the viable technologies in the new millennium has discovered successfulness in reducing undesirable problems related to power system operation. The advent of computational intelligence methods are mostly assisting to achieve high efficiency for controlling the changing of sophisticated process flow in industrials. Congestion problem in power system is a crucial issue as it leads to the smoothness of power delivery to the consumer. One of the techniques to alleviate this problem is the installation of Flexible Alternating Current Thyristor into the existing power system network. This paper presents fuzzy bee colony approach to mitigate congestion problems through TCSC installation for voltage control strategy. The bee colony optimization technique (BCO) is used for searching the optimal sizing for TCSC. Validation was conducted using the IEEE 26 Bus Reliable Test System (RTS), particle swarm optimization is used for verification purposes.

Stability index tracing for determining FACTS devices placement locations

Locating the suitable locations in power system for the purpose of Flexible Alternating Current Transmission System (FACTS) devices installation can be realized via wide variety of techniques, and commonly applied by many researchers are sensitivity analysis and optimization approach. On the other hand, there are also various power tracing techniques have been invented by researchers, but their application is only for transmission service pricing. To try a new method for locating the most suitable locations for FACTS devices placement, this paper has invented a new method for ranking the priority of buses, namely Fast Voltage Stability Index Load Tracing (FVSI-LT) via a new hybrid algorithm, Blended Crossover Continuous Ant Colony Optimization (BX-CACO). The method reflects reliable ranking results after comparison with other methods.

PSS-LL based power system stability enhancement using IPSO approach

This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning three PSS-LL parameters, a new Particle Swarm Optimization (PSO) technique called Iteration PSO (IPSO) is proposed. In this method, a new iteration best index is implemented into conventional PSO in order to enhance the quality of the solution. Based on eigenvalues and damping ratio results, it is confirmed that the proposed technique is more efficient than conventional PSO in improving the angle stability of the system. Comparison between IPSO, PSO and Evolutionary Programming (EP) optimization techniques showed that the proposed computation approach give better solution and faster computation time.

Improving power system damping using EP based PI controller

This paper presents a new stochastic optimization technique for tuning conventional PI controller parameters of a static var compensator (SVC) which controls a synchronous machine. As a type of Flexible AC Transmission Systems (FACTS) device, SVC is designed and implemented to improve the damping of a synchronous generator. Computational intelligence technique based PI controller using SVC is implemented in this study. The study involves the development of PI controller for SVC placement, while computational intelligence technique is used to optimize the values of proportional gain, KP and interval gain, KI parameters of PI controller. Validation with respect to eigenvalues determination and synchronizing and damping torque coefficients (KS and KD) value confirmed that the proposed technique is effective to improve the angle stability problem.

Hybrid ant colony technique for reactive power tracing in deregulated power system

Providing high security and reliability for a power system is compulsory for a transmission service provider (TRANSCO) as this will affect the performance in terms of stability and economy. This can only be achieved by means of ancillary services like reactive power provision. However, to cover the cost of supplying such services, determination of appropriate methods for allocating the cost to consumers (which are generation company (GENCO) and distribution company (DISCO)) without any discrimination is necessary. After struggle development performed by researchers, the new technique for allocating such cost considering fairness and free-discrimination has been proposed; that is power tracing. The recent power tracing techniques are majorly based on proportional sharing principle (PSP) and circuit theory. In addition, they are very dependent on matrix singularity and thus increasing the probability for matrix inversion failure if the matrix to be inversed is singular. To counter this weakness, this paper proposes optimization assisted reactive power tracing via hybrid ant colony algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO). After experiment on IEEE 14-bus system, it is discovered that the proposed technique can also be a potential tool for providing non-discriminatory tracing results as compared to other conventional methods.

BCO based technique for line outage identification in congestion management

In a modern urbanization metropolitan country, energy especially electrical energy is considered as an inevitable necessity because of their need have been seen apparently increase every year. Since then, the congestion in the power system had brought serious problems for the utility in particular. If the problems are not handled with care, a grisly catastrophic event is waiting, thus an appropriate method is recommended in order to explore a new approach to solve congestion issue. In this paper, congestion management with the bee colony optimisation (BCO) technique in solving the congestion problems in power system is presented. The BCO has been used in IEEE 30-Bus Reliability Test System (RTS) Bus and IEEE 26-RTS Bus to validate its capability. However for the verification purposes, other optimization such as Evolutionary Programming (EP) and Particle Swarm Optimisation Technique (PSO) are also be used.